A buyer may have the option of buying from any of a number of different sellers, as well as the option of buying any of a number of different items to meet a particular need. As a result, a buyer may seek to optimize its sourcing by identifying suitable sellers (which may include sellers offering the lowest prices) and suitable items (which may include the lowest-priced items meeting certain requirements) from among the options available to the buyer. To identify suitable sellers and items, a buyer may communicate one or more requests for quote (RFQs) to one or more sellers, receive price quotes in response to the RFQs, and compare the received price quotes. The buyer may communicate a particular RFQ to a large number of sellers and may communicate a large number of related RFQs (meaning RFQs requesting quotes for related orders) to each of these sellers. The buyer may also “shop” a large number of unrelated orders using this or similar RFQ processes. Due to the large number of communications that may be involved in traditional RFQ processes, considerable bandwidth and other network resources may be needed to support these processes where RFQs and price quotes are communicated across networks coupling buyers with sellers. Moreover, seller delays in generating price quotes, network delays in communicating price quotes, network unreliability, and other shortcomings of traditional RFQ techniques may hinder these and similar processes.